This week it is the notion that Gardasil causes infertility by inducing Primary Ovarian Failure/insufficient (POF). It is popping up on social media – again. The fact is that Gardasil does not cause infertility.

By infertility I refer to the claims of POF, which is a loss of normal ovarian function at a young age and can result in infertility. The condition affects about 1 percent of women before age 40.

If you have heard scary stuff and are a bit worried that Gardasil may put fertility at risk but you can’t be bothered reading further for the science, let me give you the short answer. No it does not. In contrast, it may just SAVE their fertility by preventing the need for invasive procedures that raise the risk for miscarriage or preterm birth, because it prevents cervical disease.

Here is my summary of the issue.

Some authors (with undisclosed conflicts of interest) have presented several case studies of young women who developed POF at varying time points following receipt of a dose of Gardasil.

They propose a biological mechanism that has not been scientifically established, in fact it is far-fetched, like Unicorns.

None of the extensive global vaccine surveillance systems have identified a signal for this condition following Gardasil.

In the large clinical trials the birth rate was the same in both vaccinated and unvaccinated which does not support that the vaccine caused infertility.

1. Can the given vaccine cause a particular adverse event?

Here we need to consider that there must be a temporal relationship. In other words the vaccine exposure must precede the occurrence of the event, but that is NOT enough on its own to answer this question. The association must reach statistical significance; there should be evidence that there is a dose relationship (more vaccine more events); the evidence should be consistent in that other studies in different settings using different methods return similar findings; the vaccine is the only cause of the event that can be found and finally; there is some biological plausibility. So, what have we got to suggest Gardasil causes infertility, or more specifically, POV, as the serpent heads are calling it?

Gardasil HPV Vaccine. Credit: melvil / Wikimedia.

The first single case of POI in association with HPV vaccine was published in 2012 by Little et al with a two further cases following in 2014 from the same authors. The first case experienced symptoms some undisclosed months (>5) after the third dose of vaccine. The second case ‘about’ a year after the third dose and the third case after the first period following the third dose. Call me cynical but that hardly fulfils the criteria above.

So what else have we got?

In 2013 a series of three cases was published by Colafrancesco et al. These six cases were then reviewed in a 2015 paper by Gruber and Shoenfeld, who for some reason do not note the time to onset of POI. For most of the cases the timing is inconsistent and more than a few months following the third dose. The authors associated the cases with a syndrome proposed by one of the senior authors, Yehuda Shoenfeld* called autoimmune/inflammatory syndrome induced by adjuvants (ASIA), or Shoenfeld’s Syndrome. No doubt this in an attempt to provide some kind of biological plausibility (I have discussed the extensive shortcomings of this previously ). What really stinks is that it appears Shoenfeld has a massive undisclosed conflict of interest in promoting his hypothesis as it would appear it may have been for the purposes of litigation. Sorry but the ASIA idea really does not fly.

I don’t want to be a complete party pooper and do concede that while an auto immune response is biologically possible and a syndrome “ASIA” has been proposed the hypothesis has not been accepted by the scientific community. No scientific evidence exists as to its validity. Among all the VAST post licensure studies of vaccines no evidence exists to support an association between these routinely used aluminium adjuvant containing vaccines and autoimmunity.

Still not seeing that this fulfils any causality assessment criteria.

Using a somewhat more scientific approach Pellegrino et al attempted to assess a potential association between POF and HPV vaccine using passive reporting data, with the denominator derived from an estimate of doses delivered. They assessed the reporting rates from the US, European and Australian passive reporting systems and found seven cases. They also evaluated the hospital discharges. Neither assessment revealed an increase in POF among the population exposed to HPV vaccine. Regardless of the findings, I must point out for the gazillianth time, that the use of passive reporting data to assess causality is not appropriate. Spontaneous reporting is only signal generating and vaccine exposure cannot be assigned. However, the hospitalisation data is less prone to reporting bias. While these authors did not find an association, this evidence in totality is weak at best.

Therefore we have no evidence to show a causal relationship and weak evidence to reject a causal relationship.

While it is fair to say no evidence exists that indicates a risk for POF in vaccinated girls we cannot know, based on individual case reports, that the vaccine did not cause this event in these particular cases. This is where the next question comes in.

2. Did the vaccine given to a particular individual cause the particular event reported?

Firstly, like the above assessment, the vaccine must precede the occurrence of the event. Tick. In these case reports this did indeed appear to be the case, at least at some point. If the fact that the cases thus far described are ill defined and do not have consistent temporal onsets, with most occurring many months, sometimes years later, does not have you doubting then lets look for more definitive proof. This is where we really see those that peddle this theory working hard. They produce all manner of meaningless clinical and laboratory data. Screeds of it. Only problem is, it shows nothing. In fact what would you look for? What would you expect to see?

Let’s go back to the first question about “can it?” At the moment we have to reject a population level association because there is no evidence that there is an association. We have no reasonable biologically plausible reasons to think that Gardasil vaccine cases POF (None within the realms of science anyway). So what should we do next?

We should move on to consider alternative explanations. By not giving due attention to other possibilities then we are doing the patient no service.

Coincidental Adverse Events
Here is a list of possible other explanations listed in the WHO assessment guidelines. Perhaps some of these are more likely to have an association with the onset of POF than a vaccine?

pre-existing illness;

newly acquired illness;

spontaneous occurrence of an event without known risk factors;

emergence of a genetically programmed disease;

other exposures to drugs or toxins prior to the event;

surgical or other trauma that leads to a complication;

a manifestation of, or complication of, a coincidental infection that was present before or at the time of immunization, or was incubating, but was not apparent at the time of immunization.

Think about it.

Now here is what I believe is the clincher.

3. Will it?

There is no evidence to support a link between POF and Gardasil vaccine in the literature. In contrast, the pivotal clinical trials found no difference in the pregnancy rate between vaccinated and placebo groups. See below a table summarising. Oh, and just in case someone says ‘but it is the aluminium what is doing it and some of the placebos contained aluminium,’ consider that most of the world’s population have received vaccines containing tiny amounts of aluminium, the most common metallic element, you find it throughout our environment, in food and water including breastmilk. No sign of infertility.

Pregnancy Outcomes in the Phase III Program Database as of 11 Nov 2005.

There is no scientific evidence that Gardasil causes POF or infertility. On the contrary, the vaccine prevents cervical abnormalities that necessitate invasive procedures that can result in pregnancy complications.

]]>https://sciblogs.co.nz/diplomaticimmunity/2017/02/14/hpv-vaccine-not-destroy-fertility/feed/29Are we getting safe medicines?https://sciblogs.co.nz/kidney-punch/2013/03/22/are-we-getting-safe-medicines/
https://sciblogs.co.nz/kidney-punch/2013/03/22/are-we-getting-safe-medicines/#commentsThu, 21 Mar 2013 22:44:21 +0000http://100dialysis.wordpress.com/?p=619Continue reading »]]>Do you read the small print about side effects? Does your doctor tell you? What are the chances that taking a medicine will kill you or make you ill in an entirely new way?

This last question is one reason why trials are run before a medicine is approved for use. However, there is an inherent flaw in the system. No matter how many people are in a trial there is a chance that a side effect will be missed. Consider this: Imagine choosing one school class out of all the classes in the country to check the prevalence of albinism. Given only about 1 in 17,000 people have albinism then you can imagine that it is unlikely that you will find an albino person. However, you may find a red haired child because the prevalence is much higher. If, though, you check a whole school you may still not find albinism. Can you, then, conclude there is none? No, because even if the school has 2000 pupils there is only a small chance of finding the condition. Quite simply, the rarer the condition the more pupils need to be checked. In terms of drugs, the rarer the side effect the more people need testing.

However, the difference between new drugs and our analogy is that trials are looking for unknown side effects. What this means, is that a statistician can turn things around and say that for a trial of a given size if a side-effect is not seen what is the maximum prevalence of that side effect. If, for example, you only cared if the drug increased the risk of a side-effect by more than 5 times (Relative Risk = 5) compared with those not taking the drug, and the event was relatively rare (say 1 in 5000), then you would need to have a trial with 14,707 people taking the drug and another 14,707 in a control group (e.g. taking a drug already used to treat the disease) in order to be reasonably certain that the new drug did not increase the risk by more than 5 times (see the table). The side-effect you are interested in may be serious (eg kidney cancer), but if the drug is saving many lives in the first place (eg a drug that suppresses the immune system and allows transplants to take place), then it may be an “acceptable” risk. The point is that trials must be of sufficient size to measure an “acceptable risk.”

In a recent article published in PLOS Medicine (see here) researchers looked at the number of participants in trials of drugs approved by the European Medicines Agency over the last decade. Quite shocking is that for medicines intended for long term use (Chronic diseases) nearly 20% were approved even though they did not meet the Agency’s own criteria for numbers of patients in studies, and these were very very low numbers indeed (300 over 6 months)! Only about 10% of studies had sufficient participants to pick up on a risk of greater than 5 fold with an incidence of more than 1 in 1000. This highlights why it is absolutely imperative that there are further ongoing studies monitoring side effects of drugs once the drug has been approved. Anyone who has read Ben Goldacre’s book “Bad Pharma” will know such studies are often poorly done if done at all. How do we ensure such studies are done? Do we legislate that drug companies do them (potential bias here), or do we make sure we have a well trained, adequately funded independent group of scientists able to do this? If you think the latter, let your MP know! In the meantime, let the medicated beware.